基于差分进化算法的无人潜航器水平面水动力参数辨识研究

Horizontal plane hydrodynamic parameters identification of Unmanned Underwater Vehicle based on Differential Evolution algorithm

针对无人潜航器(Unmanned Underwater Vehicle,UUV)水动力参数试验和理论计算的困难性及以往辨识方法优化结果趋于局部最优解的缺点,提出一种基于差分进化(Differential Evolution,DE)算法的UUV水动力参数辨识方法,针对“海翔500X”进行动力学建模分析的基础上,利用该方法对其水平面运动水动力参数进行辨识,与实际值进行比较后,辨识误差在允许范围之内。将辨识结果与粒子群优化(Particle Swarm Optimization,PSO)算法及最小二乘(Least Square,LS)算法的辨识结果进行比较,仿真结果表明,应用差分进化算法的参数辨识结果明显优于其他对比方法,证明了算法的有效性与合理性。利用辨识结果对水平回转运动进行预报,差分进化算法的预报回转轨迹与实验数据最为吻合,表明该方法可行、准确,对无人潜航器的水动力参数辨识问题具有指导意义。

Aiming at the difficulty of hydrodynamic parameters test and theoretical calculation of Unmanned Underwater Vehicle(UUV)and the shortcoming that the optimization results of previous identification methods tend to local optimal solutions,an algorithm based on Differential Evolution(DE)is proposed.Based on the dynamic modeling analysis of"Haixiang 500X",this method is used to identify the hydrodynamic parameters of its horizontal plane motion after comparing with the actual value,the identification error is within the allowable range.The identification results were compared with the identification results of the Particle Swarm Optimization(PSO)algorithm and the Least SQuare(LS)algorithm.The simulation results show that the parameter identification results using the Differential Evolution algorithm are significantly better than other comparison methods,which shows the effectiveness and rationality of the algorithm.Using the identification results to predict the horizontal turning motion,the predicted turning trajectory of the Differential Evolution algorithm is the most consistent with the experimental data.The results show that the method is feasible and accurate,and has guiding significance for the hydrodynamic parameter identification of the Unmanned Underwater Vehicle.